Jobs at BlockTech

Own and evolve BlockTech’s self-hosted data infrastructure for trading systems, including low-latency ingestion, Kafka and NATS streaming, PostgreSQL, ClickHouse, and Iceberg storage. Ensure data reliability through gap detection, repair, schema evolution, capacity planning, and failure handling. Partner with trading and research teams, lead projects from concept through production, establish technical standards, mentor engineers, and influence platform architecture.

Quantitative Research Intern supporting BlockTech’s Delta One algorithmic trading team in Singapore. The intern will complete an end-to-end research project from design through deployment, work with perpetual futures, spot markets, and real-world trading data, and collaborate with quantitative researchers and software engineers. Responsibilities include market and company training, research development, understanding trading infrastructure, and contributing to automated trading systems.

This 8–10 week internship involves completing an end-to-end quantitative research project for the option pricing team, from design through deployment. The intern will receive training in financial markets and algorithmic trading, collaborate with quantitative researchers and software engineers, and develop an understanding of trading, market data, infrastructure, and research systems.

Software Engineer Interns will complete an end-to-end project from design through deployment, working with production data and systems in a small Singapore-based team. Responsibilities include participating in financial markets training, collaborating with engineers, traders, and researchers, and building fast, reliable software for automated trading systems. Interns will receive mentorship and may convert to a full-time role after graduation based on performance.

Software engineering interns will complete an end-to-end project from design through deployment, working with production data and 24/7 trading systems. They will participate in technical and financial-market training, collaborate in a small engineering team, and learn from experienced engineers while contributing to automated trading technology.

Senior, hands-on quant researcher owning end-to-end research from hypothesis, dataset construction, feature engineering, model training, backtesting, and live deployment. Collaborate with traders and engineers, monitor and iterate production models, mentor junior researchers, and shape research and trading infrastructure.

Conduct end-to-end quantitative research for crypto derivatives and spot markets: build datasets, engineer features, train and backtest ML models, deploy and monitor production models, and collaborate with traders and engineers to convert research into trading strategies.

Develop, backtest, deploy, and monitor ML-driven trading models and signals for crypto spot and derivatives markets; collaborate with traders and engineers to move research ideas into production.

Manage Delta1 positions across venues, read live market flow, tune and intervene in automated trading systems, improve execution via data analysis, and design trading tools while collaborating with researchers and engineers.

Maintain and evolve position, trade, and PnL systems; build high-throughput real-time services and data pipelines; integrate exchanges and prime brokers; model instruments, implement self-healing discrepancy detection, develop hedging infrastructure, and deliver reporting for traders, risk, and compliance.

Own and evolve core trading systems ensuring correctness of positions, PnL, instruments, and real-time data flows. Architect low-latency, high-throughput services, lead exchange integrations, build self-healing detection/repair flows, design hedging infrastructure, deliver reporting, and mentor engineers while setting technical standards.

Own and maintain position, trade, and PnL systems; build hedging, Greeks, margin and early-exercise models; produce risk views and regulatory/internal reports; support traders; debug and resolve live production discrepancies.

Build and own production infrastructure that turns research models into live trading systems: data pipelines, backtesting, deployment, monitoring. Convert research prototypes to robust, performant production code, collaborate with researchers and traders, maintain reliability and low latency, and improve tooling and standards across the trading floor.